{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%capture timeit_results\n",
    "# Regular Python\n",
    "%timeit python_list_1 = range(1,1000)\n",
    "python_list_1 = range(1,1000)\n",
    "python_list_2 = range(1,1000)\n",
    "\n",
    "#Numpy\n",
    "%timeit numpy_list_1 = np.arange(1,1000)\n",
    "numpy_list_1 = np.arange(1,1000)\n",
    "numpy_list_2 = np.arange(1,1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000000 loops, best of 3: 223 ns per loop\n",
      "The slowest run took 12.37 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "1000000 loops, best of 3: 996 ns per loop\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(timeit_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%capture timeit_python\n",
    "%%timeit\n",
    "# Regular Python\n",
    "[(x + y) for x, y in zip(python_list_1, python_list_2)]\n",
    "[(x - y) for x, y in zip(python_list_1, python_list_2)]\n",
    "[(x * y) for x, y in zip(python_list_1, python_list_2)]\n",
    "[(x / y) for x, y in zip(python_list_1, python_list_2)];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 loops, best of 3: 273 us per loop\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print( timeit_python)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%capture timeit_numpy\n",
    "%%timeit\n",
    "#Numpy\n",
    "numpy_list_1 + numpy_list_2\n",
    "numpy_list_1 - numpy_list_2\n",
    "numpy_list_1 * numpy_list_2\n",
    "numpy_list_1 / numpy_list_2;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 62.71 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "100000 loops, best of 3: 5.26 us per loop\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print( timeit_numpy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "!pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%lsmagic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RGAHgvdzn1Tu313897+gDQKtcI5ENYGV5NejjIboAXThKMALGANwAtAWwEUBoST15AN1y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\nc/mllJWVodcfuzLsvzui0SjDw8P4fD7y8vImxY7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UL8bxwQtkZAsqL/sUr9/5ExZ/65us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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2613b1d4908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Demo of bar plot on a polar axis.\n",
    "\"\"\"\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "N = 20\n",
    "theta = np.linspace(0.0, 2 * np.pi, N, endpoint=False)\n",
    "radii = 10 * np.random.rand(N)\n",
    "width = np.pi / 4 * np.random.rand(N)\n",
    "\n",
    "ax = plt.subplot(111, projection='polar')\n",
    "bars = ax.bar(theta, radii, width=width, bottom=0.0)\n",
    "\n",
    "# Use custom colors and opacity\n",
    "for r, bar in zip(radii, bars):\n",
    "    bar.set_facecolor(plt.cm.jet(r / 10.))\n",
    "    bar.set_alpha(0.5)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<HTML>\n",
       "   <HEAD>\n",
       "      <TITLE>\n",
       "         A Small Hello \n",
       "      </TITLE>\n",
       "   </HEAD>\n",
       "<BODY>\n",
       "   <H1>Hi</H1>\n",
       "   <P>This is very minimal \"hello world\" HTML document.</P> \n",
       "</BODY>\n",
       "</HTML>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%HTML \n",
    "<HTML>\n",
    "   <HEAD>\n",
    "      <TITLE>\n",
    "         A Small Hello \n",
    "      </TITLE>\n",
    "   </HEAD>\n",
    "<BODY>\n",
    "   <H1>Hi</H1>\n",
    "   <P>This is very minimal \"hello world\" HTML document.</P> \n",
    "</BODY>\n",
    "</HTML>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/IVrGz8w0H8c\" frameborder=\"0\" allowfullscreen></iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%HTML\n",
    "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/IVrGz8w0H8c\" frameborder=\"0\" allowfullscreen></iframe>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"hello\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100000000 loops, best of 3: 10.6 ns per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "10*10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## another sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
